/*
 * Copyright (C) 2009 The Android Open Source Project
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#ifndef PINYINIME_INCLUDE_NGRAM_H__
#define PINYINIME_INCLUDE_NGRAM_H__

#include <stdio.h>
#include <stdlib.h>
#include "./dictdef.h"

namespace ime_pinyin {

    typedef unsigned char CODEBOOK_TYPE;

    static const Size_t kCodeBookSize = 256;

    class NGram {
        public:
            // The maximum score of a lemma item.
            static const LmaScoreType kMaxScore = 0x3fff;

            // In order to reduce the storage size, the original log value is amplified by
            // kScoreAmplifier, and we use LmaScoreType to store.
            // After this process, an item with a lower score has a higher frequency.
            static const int kLogValueAmplifier = -800;

            // System words' total frequency. It is not the real total frequency, instead,
            // It is only used to adjust system lemmas' scores when the user dictionary's
            // total frequency changes.
            // In this version, frequencies of system lemmas are fixed. We are considering
            // to make them changable in next version.
            static const Size_t kSysDictTotalFreq = 100000000;

        private:

            static NGram *instance_;

            bool initialized_;
            Size_t idx_num_;

            Size_t total_freq_none_sys_;

            // Score compensation for system dictionary lemmas.
            // Because after user adds some user lemmas, the total frequency changes, and
            // we use this value to normalize the score.
            float sys_score_compensation_;

#ifdef ___BUILD_MODEL___
            double *freq_codes_df_;
#endif
            LmaScoreType *freq_codes_;
            CODEBOOK_TYPE *lma_freq_idx_;

        public:
            NGram();
            ~NGram();

            static NGram &get_instance();

            bool save_ngram ( FILE *fp );
            bool load_ngram ( FILE *fp );

            // Set the total frequency of all none system dictionaries.
            void set_total_freq_none_sys ( Size_t freq_none_sys );

            float get_uni_psb ( LemmaIdType lma_id );

            // Convert a probability to score. Actually, the score will be limited to
            // kMaxScore, but at runtime, we also need float expression to get accurate
            // value of the score.
            // After the conversion, a lower score indicates a higher probability of the
            // item.
            static float convert_psb_to_score ( double psb );

#ifdef ___BUILD_MODEL___
            // For constructing the unigram mode model.
            bool build_unigram ( LemmaEntry *lemma_arr, Size_t num,
                                 LemmaIdType next_idx_unused );
#endif
    };
}

#endif  // PINYINIME_INCLUDE_NGRAM_H__
